| ID | 原文 | 译文 |
| 8164 | 在估计混合矩阵时,首先利用观测信号的实部与虚部方向一致性检测时频单源点,在采用S变换构造时频比矩阵的基础上,利用方差法实现了混合矩阵估计; | Estimate the mixing matrix, the first use of the real part and imaginary part of direction observation signal time-frequency monophyletic point consistency detection, when the frequency ratio matrix constructed in the S transform, on the basis of variance method is used to realize the mixing matrix estimation; |
| 8165 | 在源信号恢复时,利用改进的子空间投影法得到源信号的时频域分离,最后可通过S逆变换得到时域分离信号,从而实现了欠定条件下的跳频网台分选。 | The source signal is restored, the use of improved subspace projection method to get the source signal separation time and frequency domain, the final separation can be obtained by inverse transformation S time domain signals, so as to realize the underdetermined fh network under the condition of separation. |
| 8166 | 仿真结果表明,该方法有效实现了混合跳频信号在欠定条件下的网台分选且适用于跳频同步或异步组网方式,提高了分选性能和抗噪性能。 | The simulation results show that this method is effective to realize the mixing of frequency hopping signals under the underdetermined conditions and is suitable for the network station sorting fh synchronous or asynchronous network mode, to improve the separation performance and antinoise performance. |
| 8167 | 在平台-任务关系优化设计中,考虑单个任务资源分配过程中平台资源冗余度对后续任务分配的影响,分析优化设计过程的约束条件,构建了以最大任务执行精度与最小资源冗余度为综合目标函数的平台-任务关系设计的问题模型,并使用基于m-best算法与rollout策略的方法对问题模型进行求解。 | In optimization design of platform - task, consider a single task in the process of the allocation of resources platform resource redundancy influence on subsequent task allocation, optimal design process of constraint conditions, constructed the tasks performed with maximum precision and minimum redundancy for the resources of the objective function of the platform - task relations about the design of the model, and use the method based on m - best algorithm and rollout strategy for solving problem model. |
| 8168 | m-best算法生成单个任务的m个平台分配方案,rollout策略用于均衡不同优先级任务之间的任务执行精度。 | M - the best algorithm to generate a single task m platform scheme, rollout strategy used in task execution precision of the equilibrium between different priority task. |
| 8169 | 最后,分别通过特殊算例和一般算例验证所提优化设计方法的优越性,算例的结果表明,使用该优化设计方法能够使高优先权任务的资源冗余度降低,从而使得整体任务执行精度提高。 | Finally, respectively, through the special case and general examples verify the superiority of the proposed optimal design method, the results of numerical examples show that using the optimization design method can make the resources of the high priority task redundancy is reduced, so as to make the whole task execution accuracy improved. |
| 8170 | 在舰船升沉信息的实时测量过程中,升沉滤波器实现了低频衰减和特定频段二次积分,但其存在输出相位超前的问题,并且超前相位的大小随输入信号频率变化。 | In the process of ship heave information real-time measurement, heave filter to achieve the low frequency attenuation and quadratic integral specific frequency, but its output phase advance problem, and the size of the leading phase change with the input signal frequency. |
| 8171 | 首先分析了升沉滤波器的误差特性,然后针对相位超前和噪声、零偏对系统影响的问题,提出了基于带限傅里叶线性组合(band-limited multiple Fourier linear combiner,BMFLC)算法校正滤波器输出的方法,并分析了算法中参数的选取和算法的计算量,实现了在抑制噪声和零偏的影响下对滤波器的输出进行幅度和相位补偿,进而提高了测量精度。 | First analyzes the characteristics of the error of the heave filter, and then based on phase advance and noise, zero impact on the system problem, was proposed based on linear combination band-limited Fourier (band - limited multiple Fourier linear combiner, BMFLC) algorithm correction output filter method, and the selection of parameters in the algorithm is analyzed and calculation of the algorithm and implements under the influence of noise and zero output of filter and phase compensation, thus improving the accuracy of measurement. |
| 8172 | 仿真结果表明,提出的基于BMFLC算法的舰船升沉测量方法对升沉滤波器的输出进行了补偿,能够很好地解决超前相位误差和噪声、零偏影响的问题,实现了舰船升沉信息测量的实时性和准确性。 | The simulation results show that the proposed ship heave measurement method based on BMFLC algorithm of heave compensation, the output of filter can effectively solve the leading phase error and the influence of noise, zero bias problem, has realized the ship heave information real-time and accuracy of measurement. |
| 8173 | 在纠错输出编码(error-correcting output code,ECOC)多类分类中,当待识别样本的真实类别不属于对应二类子类划分时,训练得到的基分类器将不具备对此类样本进行分类的能力,此时的基分类器在解码融合时面临着non-competence问题。 | In error correcting output codes (error - correcting the output code, ECOC) more class category, when real category of unknown sample does not belong to the corresponding second subclass, obtained the base classifier training will do not have the ability to categorize such samples, at this point the base classifier in the decoding of fusion when faced with the problem of non - competence. |